The lack of GPS signal in the underwater environment poses limitations in terms of localization and navigation of mobile robots. Strategies based on acoustic localization systems are employed to improve underwater navigation. In this paper we describe a first step towards the development of a marine system of systems involving autonomous mobile nodes. The approach relies on communication networking between an Autonomous Surface Vehicle (ASV), equipped with an Ultra Short BaseLine (USBL) device, and an Autonomous Underwater Vehicle (AUV). An active acoustic communication protocol prioritizes the AUV positioning rate, whereas a model-based navigation filter handles the delayed measurements caused by the acoustic communication latency. The system has been tested in a real marine environment to analyze its behavior and the quality of the navigation estimation. The experimental results show that the navigation algorithm on-board the AUV provides an estimate of its position with an error of a few meters with respect to the GPS ground-truth, over a total path of approximately 210m, exploiting acoustic positioning data provided by the ASV in order to limit drift problems.

An accurate orientation estimation is a primary requirement in autonomous navigation tasks of mobile robots, especially when such operation is involved in the solution of the position estimation problem (e.g. dead reckoning navigation systems). This is the case of Autonomous Underwater Vehicles (AUVs), subject of this paper; for this class of robots, a complete attitude estimation system based on the adaptation of a Nonlinear Complementary Filter (NCF) is proposed. The presented filter fuses the measurements of an Inertial Measurement Unit (IMU) comprising magnetometers. The integration of a single-axis Fibre Optic Gyroscope (FOG) is evaluated to overcome issues due to magnetic disturbances. In addition, a calibration procedure for magnetometers to be exploited within the attitude estimation filter is proposed. The whole system has been experimentally validated and tested on the University of Florence Typhoon AUV; the results prove that the proposed approach allows to obtain a reliable orientation estimate even in the presence of external unpredictable disturbances.

Many dynamic simulators have been developed in the last thirty years for different types of vehicles. Flight simulators and drive simulators are very well known examples. This paper describes the design and implementation of a dynamic simulator for the testing of inertial sensors devoted to vehicle navigation through a Hardware-In-The-Loop test rig composed of an industrial robot and a commercially available Inertial Measurement Unit (IMU). The authors are developing an innovative localization algorithm for railway vehicles which integrates inertial sensors with tachometers. The opportunity to set up a testing simulator capable of replicating in a realistic fashion the dynamic effects of the vehicle motion on inertial sensors allows to avoid expensive on board acquisitions and to speed up algorithm tuning. The real-time control architecture featured by the available industrial robot allows to precisely specify and execute motion trajectories with tight path and time law constraints required by the application at hand.